Systems and methods for dynamic messaging campaign

ABSTRACT

Methods and systems for generating a messaging campaign are described. A first phase of the campaign is conducted using a first set of parameters for delivering a first message to a first group of intended recipients via a first distribution channel. Based on analysis of online activity associated with one or more members of the first group, a second set of parameters is determined for a second phase of the messaging campaign. The second set of parameters define a change to the first set of parameters.

FIELD

The present disclosure relates to methods and systems for generatingmessaging campaigns, including messaging campaigns related toe-commerce.

BACKGROUND

Marketers and merchants often use messaging campaigns to communicatecertain message contents to a desired demographic. For stores having anonline presence (e.g., an e-commerce store), such messaging campaignsoften include messages sent via electronic channels, such as via emailor social media.

Conventional techniques for generating and managing messaging campaigns(e.g., email marketing campaigns) have limited flexibility. For example,a conventional messaging campaign typically relies on the initiator ofthe campaign (e.g., the human marketer or merchant) to define theparameters of the messaging campaign (e.g., the intended recipients, themessage content, and the distribution channel). Once defined, themessaging campaign is carried out accordingly. However, reliance on thehuman initiator to define the parameters of the campaign can result inthe same parameters being used over and over again, due to human habit,or can result in selected parameters that do not align well with eachother or with the preferences of the intended recipients.

It would be useful to provide a more dynamic way to generate and carryout a messaging campaign, which may help to avoid over-reliance onhuman-submitted campaign parameters.

SUMMARY

The present disclosure describes various examples which may enable moredynamic generation of messaging campaigns. In some examples, a set ofrecommended parameters for a messaging campaign may be automaticallygenerated, based on a set of default parameters and/or user-submittedparameters. Different sub-groups may be identified within a group ofintended recipients, and different recommended campaign parameters maybe automatically generated to better direct the campaign towards thedifferent sub-groups.

In some examples, the parameters of the messaging campaign can bedynamically adjusted throughout the timeline of the campaign. Forexample, depending on how different recipients respond to a first phaseof the campaign, the recommended parameters for carrying out a secondphase of the campaign may be automatically and dynamically adjusted.

The examples described herein may be implemented in the context of ane-commerce platform, or may be made available for use outside of thee-commerce platform.

Some examples described herein may be described in the context of emailcommunications. However, it should be understood that different forms ofelectronic communications (e.g., email, text messaging, social mediaprivate or public messages, etc.) may be within the scope of the presentdisclosure.

The examples described herein may be applicable to messaging campaignsin a variety of contexts, including for messaging campaigns related tomarketing for e-commerce (e.g., for stores and/or merchants having anonline presence).

In some examples, the present disclosure describes a system including aprocessor in communication with a storage. The processor is configuredto execute instructions in the storage to cause the system to: conductat least a first phase of a messaging campaign, the first phaseincluding a first set of parameters for delivering a first message to atleast a first group of intended recipients, the first set of parametersdefining at least the first group and a respective first distributionchannel; determine, based on analysis of online activity associated withone or more members of the first group, the online activity beingassociated with a store, a second set of parameters for a second phaseof the messaging campaign, the second set of parameters defining achange to the first set of parameters for delivering a second message tothe one or more members; and generate a recommendation to conduct thesecond phase of the messaging campaign for the one or more members usingthe second set of parameters.

In some examples, the present disclosure describes a method including:conducting at least a first phase of a messaging campaign, the firstphase including a first set of parameters for delivering a first messageto at least a first group of intended recipients, the first set ofparameters defining at least the first group and a respective firstdistribution channel; determining, based on analysis of online activityassociated with one or more members of the first group, the onlineactivity being associated with a store, a second set of parameters for asecond phase of the messaging campaign, the second set of parametersdefining a change to the first set of parameters for delivering a secondmessage to the one or more members; and generating a recommendation toconduct the second phase of the messaging campaign for the one or moremembers using the second set of parameters.

In some examples, the present disclosure describes a computer readablemedium having computer-executable instructions stored thereon. Theinstructions, when executed by a processor of a system, causes thesystem to: conduct at least a first phase of a messaging campaign, thefirst phase including a first set of parameters for delivering a firstmessage to at least a first group of intended recipients, the first setof parameters defining at least the first group and a respective firstdistribution channel; determine, based on analysis of online activityassociated with one or more members of the first group, the onlineactivity being associated with a store, a second set of parameters for asecond phase of the messaging campaign, the second set of parametersdefining a change to the first set of parameters for delivering a secondmessage to the one or more members; and generate a recommendation toconduct the second phase of the messaging campaign for the one or moremembers using the second set of parameters.

In any of the above examples, the analysis of the online activity mayinclude analysis of at least one of: online activity associated with afirst store associated with the messaging campaign, or online activityassociated with a second store not associated with the messagingcampaign.

In any of the above examples, the online activity may be associated witha purchase of a first offering associated with the messaging campaign.

In any of the above examples, the second set of parameters may bedetermined to suppress promotion of the first offering to the one ormore members in the second phase of the messaging campaign.

In any of the above examples, determine the second set of parameters maybe determined to promote a second offering, that is related to the firstoffering, to the one or more members in the second phase of themessaging campaign.

In any of the above examples, the one or more members may define asubgroup of the first group. The second phase of the messaging campaignmay be conducted according to the second set of parameters for thesubgroup; and The first phase of the messaging campaign may continue tobe conducted according to the first set of parameters for a remainder ofthe first group.

In any of the above examples, the one or more members may define asubgroup of the first group. The second phase of the messaging campaignmay be conducted for the subgroup, according to the second set ofparameters; and the second phase of the messaging campaign may beconducted for a remainder of the first group according to a third set ofparameters.

In any of the above examples, the second set of parameters may bedefined for conducting the messaging campaign to a second group ofintended recipients. The one or more members may be reassigned to thesecond group.

In any of the above examples, the online activity may include at leastone of: a page view event; a purchase transaction event; an offeringsearch event; or a product review event.

In any of the above examples, the change defined by the second set ofparameters may include at least one of: a change in distributionchannel; a change in message content; a change in message timing; achange in number of messages; or a change in incentive.

In any of the above examples, the online activity may be associated witha second distribution channel; and the second set of parameters may bedetermined to deliver the second message using the second distributionchannel.

In any of the above examples, the recommendation may be automaticallyimplemented to conduct the second phase of the messaging campaign forthe one or more members using the second set of parameters.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made, by way of example, to the accompanyingdrawings which show example embodiments of the present application, andin which:

FIG. 1 is a block diagram of an example e-commerce platform, in whichexamples described herein may be implemented;

FIG. 2 is an example homepage of an administrator, which may be accessedvia the e-commerce platform of FIG. 1;

FIG. 3 is another block diagram of the e-commerce platform of FIG. 1,showing some details related to application development;

FIG. 4 shows an example data flow that may take place when a purchase ismade using the e-commerce platform of FIG. 1;

FIG. 5 is a block diagram illustrating an example implementation of thee-commerce platform of FIG. 1;

FIG. 6 is another block diagram of the e-commerce platform of FIG. 1,showing some details related to a messaging campaign engine;

FIG. 7 is a flowchart illustrating an example method for generating amessaging campaign;

FIG. 8 is a schematic illustration of a simplified example of aspects ofthe method of FIG. 7;

FIG. 9 is a flowchart illustrating another example method for generatinga messaging campaign; and

FIGS. 10A and 10B are schematic illustrations of simplified examples ofaspects of the method of FIG. 9.

Similar reference numerals may have been used in different figures todenote similar components.

DESCRIPTION OF EXAMPLE EMBODIMENTS

The present disclosure will be described in the context of an e-commerceplatform, discussed below. However, it should be understood that thisdiscussion is only for the purpose of illustration and is not intendedto be limiting. Further, it should be understood that the presentdisclosure may be implemented in other contexts, and is not necessarilylimited to implementation in an e-commerce platform.

With reference to FIG. 1, an embodiment e-commerce platform 100 isdepicted for providing merchant products and services to customers.While the disclosure throughout contemplates using the apparatus,system, and process disclosed to purchase products and services, forsimplicity the description herein will refer to products or offerings.All references to products or offerings throughout this disclosureshould also be understood to be references to products and/or services,including physical products, digital content, tickets, subscriptions,services to be provided, and the like.

While the disclosure throughout contemplates that a “merchant”, a“marketer” and a “customer” may be more than individuals, for simplicitythe description herein may generally refer to merchants, marketers andcustomers as such. All references to merchants, marketers and customersthroughout this disclosure should also be understood to be references togroups of individuals, companies, corporations, computing entities, andthe like, and may represent for-profit or not-for-profit exchange ofproducts. Further, while the disclosure throughout refers to“merchants”, “marketers” and “customers”, and describes their roles assuch, it should be understood that aspects of the e-commerce platform100 may be more generally available to support users in an e-commerceenvironment, and all references to merchants, marketers and customersthroughout this disclosure should also be understood to be references tousers, such as where a user is a merchant-user (e.g., a seller,retailer, wholesaler, or provider of products), a marketer-user (e.g., amarketing agent, an external marketing service provider, or aself-marketing merchant), a customer-user (e.g., a buyer, purchaseagent, or user of products), a prospective user (e.g., a user browsingand not yet committed to a purchase, a user evaluating the e-commerceplatform 100 for potential use in marketing and selling products, andthe like), a service provider user (e.g., a shipping provider 112, afinancial provider, and the like), a company or corporate user (e.g., acompany representative for purchase, sales, or use of products; anenterprise user; a customer relations or customer management agent, andthe like), an information technology user, a computing entity user(e.g., a computing bot for purchase, sales, or use of products), and thelike. Further, it should be understood that any individual or group ofindividuals may play more than one role and may fit more than one labelin the e-commerce environment. For example, a merchant may also be amarketer, or a corporate user may also be a customer.

The e-commerce platform 100 may provide a centralized system forproviding merchants with online resources for managing their business.Merchants may utilize the e-commerce platform 100 for managing commercewith customers, such as by implementing an e-commerce experience withcustomers through an online store 138, through channels 110, throughpoint of sale (POS) devices 152 in physical locations (e.g., a physicalstorefront or other location such as through a kiosk, terminal, reader,printer, 3D printer, and the like), by managing their business throughthe e-commerce platform 100, by interacting with customers through acommunications facility 129 of the e-commerce platform 100, or anycombination thereof.

The online store 138 may represent a multitenant facility comprising aplurality of virtual storefronts 139. In various embodiments, merchantsmay manage one or more storefronts 139 in the online store 138, such asthrough a merchant device 102 (e.g., computer, laptop computer, mobilecomputing device, and the like), and offer products to customers througha number of different channels 110 (e.g., an online store 138; aphysical storefront through a POS device 152; electronic marketplace,through an electronic buy button integrated into a website or socialmedia channel such as on a social network, social media page, socialmedia messaging system; and the like). A merchant may sell acrosschannels 110 and then manage their sales through the e-commerce platform100. A merchant may sell in their physical retail store, at pop ups,through wholesale, over the phone, and the like, and then manage theirsales through the e-commerce platform 100. A merchant may employ all orany combination of these, such as maintaining a business through aphysical storefront utilizing POS devices 152, maintaining a virtualstorefront 139 through the online store 138, and utilizing thecommunications facility 129 to leverage customer interactions andanalytics 132 to improve the probability of sales, for example.

In various embodiments, a customer may interact through a customerdevice 150 (e.g., computer, laptop computer, mobile computing device,and the like), a POS device 152 (e.g., retail device, a kiosk, anautomated checkout system, and the like), or any other commerceinterface device known in the art. The e-commerce platform 100 mayenable merchants to reach customers through the online store 138,through POS devices 152 in physical locations (e.g., a merchant'sstorefront or elsewhere), to promote commerce with customers throughdialog via electronic communication, and the like, providing a systemfor reaching customers and facilitating merchant services for the realor virtual pathways available for reaching and interacting withcustomers.

In various embodiments, and as described further herein, the e-commerceplatform 100 may be implemented through a processing facility includinga processor and a memory, the processing facility storing a set ofinstructions that, when executed, cause the e-commerce platform 100 toperform the e-commerce and support functions as described herein. Theprocessing facility may be part of a server, client, networkinfrastructure, mobile computing platform, cloud computing platform,stationary computing platform, or other computing platform, and provideelectronic connectivity and communications between and amongst theelectronic components of the e-commerce platform 100, merchant devices102, payment gateways 106, application development 108, channels 110,shipping providers 112, customer devices 150, POS devices 152, and thelike. The e-commerce platform 100 may be implemented as a cloudcomputing service, a software as a service (SaaS), infrastructure as aservice (IaaS), platform as a service (PaaS), desktop as a Service(DaaS), managed software as a service (MSaaS), mobile backend as aservice (MBaaS), information technology management as a service(ITMaaS), and the like, such as in a software and delivery model inwhich software is licensed on a subscription basis and centrally hosted(e.g., accessed by users using a thin client via a web browser, accessedthrough by POS devices, and the like). In various embodiments, elementsof the e-commerce platform 100 may be implemented to operate on variousplatforms and operating systems, such as iOS, Android, over theinternet, and the like.

In various embodiments, storefronts 139 may be served by the e-commerceplatform 100 to customers (e.g., via customer devices 150), wherecustomers can browse and purchase the various products available (e.g.,add them to a cart, purchase immediately through a buy-button, and thelike). Storefronts 139 may be served to customers in a transparentfashion without customers necessarily being aware that it is beingprovided through the e-commerce platform 100 (rather than directly fromthe merchant). Merchants may use a merchant configurable domain name, acustomizable HTML theme, and the like, to customize their storefront139. Merchants may customize the look and feel of their website througha theme system, such as where merchants can select and change the lookand feel of their storefront 139 by changing their theme while havingthe same underlying product and business data shown within thestorefront's product hierarchy. Themes may be further customized througha theme editor, a design interface that enables users to customize theirwebsite's design with flexibility. Themes may also be customized usingtheme-specific settings that change aspects, such as specific colors,fonts, and pre-built layout schemes. The online store may implement abasic content management system for website content. Merchants mayauthor blog posts or static pages and publish them to their storefront139 and/or website 104, such as through blogs, articles, and the like,as well as configure navigation menus. Merchants may upload images(e.g., for products), video, content, data, and the like to thee-commerce platform 100, such as for storage by the system. In variousembodiments, the e-commerce platform 100 may provide functions forresizing images, associating an image with a product, adding andassociating text with an image, adding an image for a new productvariant, protecting images, and the like.

As described herein, the e-commerce platform 100 may provide merchantswith transactional facilities for products through a number of differentchannels 110, including the online store 138, over the telephone, aswell as through physical POS devices 152 as described herein. Thee-commerce platform 100 may provide business support services 116, anadministrator component 114, and the like associated with running anon-line business, such as providing a domain service 118 associated withtheir online store, payments services 120 for facilitating transactionswith a customer, shipping services 122 for providing customer shippingoptions for purchased products, risk and insurance services 124associated with product protection and liability, merchant billingservices 146, and the like. Services 116 may be provided via thee-commerce platform 100 or in association with external facilities, suchas through a payment gateway 106 for payment processing, shippingproviders 112 for expediting the shipment of products, and the like.

In various embodiments, the e-commerce platform 100 may provide forintegrated shipping services 122 (e.g., through an e-commerce platformshipping facility or through a third-party shipping carrier), such asproviding merchants with real-time updates, tracking, automatic ratecalculation, bulk order preparation, label printing, and the like.

FIG. 2 depicts a non-limiting embodiment for a home page 170 of anadministrator 114, which may show information about daily tasks, astore's recent activity, and the next steps a merchant can take to buildtheir business. In various embodiments, a merchant may log in toadministrator 114, such as from a browser or mobile device, and manageaspects of their storefront, such as viewing the storefront's recentactivity, updating the storefront's catalog, managing orders, recentvisits activity, total orders activity, and the like. In variousembodiments, the merchant may be able to access the different sectionsof administrator 114 by using the sidebar 172, such as shown on FIG. 2.Sections of the administrator may include core aspects of a merchant'sbusiness, including orders, products, and customers; sales channels,including the online store, POS, and buy button; applications installedon the merchant's account; settings applied to a merchant's storefront139 and account. A merchant may use a search bar 174 to find products,pages, or other information. Depending on the device the merchant isusing, they may be enabled for different functionality through theadministrator 114. For instance, if a merchant logs in to theadministrator 114 from a browser, they may be able to manage all aspectsof their storefront 139. If the merchant logs in from their mobiledevice, they may be able to view all or a subset of the aspects of theirstorefront 139, such as viewing the storefront's recent activity,updating the storefront's catalog, managing orders, and the like.

More detailed information about commerce and visitors to a merchant'sstorefront 139 may be viewed through acquisition reports or metrics,such as displaying a sales summary for the merchant's overall business,specific sales and engagement data for active sales channels, and thelike. Reports may include, acquisition reports, behavior reports,customer reports, finance reports, marketing reports, sales reports,custom reports, and the like. The merchant may be able to view salesdata for different channels 110 from different periods of time (e.g.,days, weeks, months, and the like), such as by using drop-down menus176. An overview dashboard may be provided for a merchant that wants amore detailed view of the store's sales and engagement data. An activityfeed in the home metrics section may be provided to illustrate anoverview of the activity on the merchant's account. For example, byclicking on a ‘view all recent activity’ dashboard button, the merchantmay be able to see a longer feed of recent activity on their account. Ahome page may show notifications about the merchant's storefront 139,such as based on account status, growth, recent customer activity, andthe like. Notifications may be provided to assist a merchant withnavigating through a process, such as capturing a payment, marking anorder as fulfilled, archiving an order that is complete, and the like.

Reference is made back to FIG. 1. The e-commerce platform may providefor a communications facility 129 and associated merchant interface forproviding electronic communications and marketing, such as utilizing anelectronic messaging aggregation facility (not shown) for collecting andanalyzing communication interactions between merchants, customers,merchant devices 102, customer devices 150, POS devices 152, and thelike, to aggregate and analyze the communications, such as forincreasing the potential for providing a sale of a product, and thelike. For instance, a customer may have a question related to a product,which may produce a dialog between the customer and the merchant (orautomated processor-based agent representing the merchant), where thecommunications facility 129 analyzes the interaction and providesanalysis to the merchant on how to improve the probability for a sale.

The e-commerce platform 100 may provide a financial facility 130 forsecure financial transactions with customers, such as through a securecard server environment 148. The e-commerce platform 100 may storecredit card information, such as in payment card industry data (PCI)environments (e.g., a card server), to reconcile financials, billmerchants, perform automated clearing house (ACH) transfers between ane-commerce platform 100 financial institution account and a merchant'sback account (e.g., when using capital), and the like. These systems mayhave Sarbanes-Oxley Act (SOX) compliance and a high level of diligencerequired in their development and operation. The financial facility 130may also provide merchants with financial support, such as through thelending of capital (e.g., lending funds, cash advances, and the like)and provision of insurance. In addition, the e-commerce platform 100 mayprovide for a set of marketing and partner services and control therelationship between the e-commerce platform 100 and partners. They alsomay connect and onboard new merchants with the e-commerce platform 100.These services may enable merchant growth by making it easier formerchants to work across the e-commerce platform 100. Through theseservices, merchants may be provided help facilities via the e-commerceplatform 100.

In various embodiments, online store 138 may support a great number ofindependently administered storefronts 139 and process a large volume oftransactional data on a daily basis for a variety of products.Transactional data may include customer contact information, billinginformation, shipping information, information on products purchased,information on services rendered, and any other information associatedwith business through the e-commerce platform 100. In variousembodiments, the e-commerce platform 100 may store this data in a datafacility 134. The transactional data may be processed to produceanalytics 132, which in turn may be provided to merchants or third-partycommerce entities, such as providing consumer trends, marketing andsales insights, recommendations for improving sales, evaluation ofcustomer behaviors, marketing and sales modeling, trends in fraud, andthe like, related to online commerce, and provided through dashboardinterfaces, through reports, and the like. The e-commerce platform 100may store information about business and merchant transactions, and thedata facility 134 may have many ways of enhancing, contributing,refining, and extracting data, where over time the collected data mayenable improvements to aspects of the e-commerce platform 100.

In various embodiments, the e-commerce platform 100 may be configuredwith a core commerce facility 136 for content management and taskautomation to enable support and services to the plurality ofstorefronts 139 (e.g., related to products, inventory, customers,orders, collaboration, suppliers, reports, financials, risk and fraud,and the like), but be extensible through applications 142 that enablegreater flexibility and custom processes required for accommodating anever-growing variety of merchant storefronts 139, POS devices 152,products, and services. For instance, the core commerce facility 136 maybe configured for flexibility and scalability through portioning (e.g.,sharding) of functions and data, such as by customer identifier, orderidentifier, storefront identifier, and the like. The core commercefacility 136 may accommodate store-specific business logic and a webadministrator. The online store 138 may represent a channel, be embeddedwithin the core commerce facility 136, provide a set of support anddebug tools that support uses for merchants, and the like. The corecommerce facility 136 may provide centralized management of criticaldata for storefronts 139.

The core commerce facility 136 includes base or “core” functions of thee-commerce platform 100, and as such, as described herein, not allfunctions supporting storefronts 139 may be appropriate for inclusion.For instance, functions for inclusion into the core commerce facility136 may need to exceed a core functionality threshold through which itmay be determined that the function is core to a commerce experience(e.g., common to a majority of storefront activity, such as acrosschannels, administrator interfaces, merchant locations, industries,product types, and the like), is re-usable across storefronts (e.g.,functions that can be re-used/modified across core functions), limitedto the context of a single storefront at a time (e.g., implementing astorefront ‘isolation principle’, where code should not be able tointeract with multiple storefronts at a time, ensuring that storefrontscannot access each other's data), provide a transactional workload, andthe like. Maintaining control of what functions are implemented mayenable the core commerce facility 136 to remain responsive, as manyrequired features are either served directly by the core commercefacility 136 or enabled by its extension/application programminginterface (API) 140 connection to applications 142. If care is not givento restricting functionality in the core commerce facility 136,responsiveness could be compromised, such as through infrastructuredegradation through slow databases or non-critical backend failures,through catastrophic infrastructure failure such as with a data centergoing offline, through new code being deployed that takes longer toexecute than expected, and the like. To prevent or mitigate thesesituations, the core commerce facility 136 may be configured to maintainresponsiveness, such as through configuration that utilizes timeouts,queues, back-pressure to prevent degradation, and the like.

Although isolating storefront data is important to maintaining dataprivacy between storefronts 139 and merchants, there may be reasons forcollecting and using cross-store data, such as for example, with anorder risk assessment system or a platform payment facility, both ofwhich require information from a majority of storefronts 139 to performwell. In various embodiments, rather than violating the isolationprinciple, it may be preferred to move these components out of the corecommerce facility 136 and into their own infrastructure within thee-commerce platform 100. For example, the data facility 134 andanalytics 132 may be located outside the core commerce facility 136.

In various embodiments, the e-commerce platform 100 may provide for aplatform payment facility 149, which is another example of a componentthat utilizes data from the core commerce facility 138 but may belocated outside so as to not violate the isolation principle. Theplatform payment facility 149 may allow customers interacting withstorefronts 139 to have their payment information stored safely by thecore commerce facility 136 such that they only have to enter it once.When a customer visits a different storefront 139, even if they've neverbeen there before, the platform payment facility 149 may recall theirinformation to enable a more rapid and correct check out. This mayprovide a cross-platform network effect, where the e-commerce platform100 becomes more useful to its merchants as more merchants join, such asbecause there are more customers who checkout more often because of theease of use with respect to customer purchases. To maximize the effectof this network, payment information for a given customer may beretrievable from a storefront's checkout, allowing information to bemade available globally across storefronts 139. It would be difficultand error prone for each storefront 139 to be able to connect to anyother storefront 139 to directly retrieve the payment information storedthere. As a result, the platform payment facility 149 may be implementedexternal to the core commerce facility 136.

For those functions that are not included within the core commercefacility 138, applications 142 provide a way to add features to thee-commerce platform 100. Applications 142 may be able to access andmodify data on a merchant's storefront 139, perform tasks through theadministrator 114, create new flows for a merchant through a userinterface (e.g., that is surfaced through extensions/API 140), and thelike. Merchants may be enabled to discover and install applications 142through application searching 208 and application recommendations 210(see FIG. 3). In various embodiments, core products, core extensionpoints, applications, and the administrator 114 may be developed to worktogether. For instance, application extension points may be built insidethe administrator 114 so that core features may be extended by way ofapplications 142, which may deliver functionality to a merchant throughthe extension/API 140.

In various embodiments, applications 142 may deliver functionality to amerchant through the extension/API 140, such as where an application 142is able to surface transaction data to a merchant (e.g., App: “Surfacemy app in mobile and web admin using the embedded app SDK”), and/orwhere the core commerce facility 136 is able to ask the application toperform work on demand (core: “App, give me a local tax calculation forthis checkout”).

Applications 142 may support storefronts 139 and channels 110, providemerchant support, integrate with other services, and the like. Where thecore commerce facility 136 may provide the foundation of services to thestorefront 139, the applications 142 may provide a way for merchants tosatisfy specific and sometimes unique needs. Different merchants willhave different needs, and so may benefit from different applications142. Applications 142 may be better discovered through the e-commerceplatform 100 through development of an application taxonomy (categories)that enable applications to be tagged according to a type of function itperforms for a merchant; through application data services that supportsearching, ranking, and recommendation models; through applicationdiscovery interfaces such as an application store, home informationcards, an application settings page; and the like.

Applications 142 may be connected to the core commerce facility 136through an extension/API layer 140, such as utilizing APIs to expose thefunctionality and data available through and within the core commercefacility 136 to the functionality of applications (e.g., through REST,GraphQL, and the like). For instance, the e-commerce platform 100 mayprovide API interfaces to merchant and partner-facing products andservices, such as including application extensions, process flowservices, developer-facing resources, and the like. With customers morefrequently using mobile devices for shopping, applications 142 relatedto mobile use may benefit from more extensive use of APIs to support therelated growing commerce traffic. The flexibility offered through use ofapplications and APIs (e.g., as offered for application development)enable the e-commerce platform 100 to better accommodate new and uniqueneeds of merchants (and internal developers through internal APIs)without requiring constant change to the core commerce facility 136,thus providing merchants what they need when they need it. For instance,shipping services 122 may be integrated with the core commerce facility136 through a shipping or carrier service API, thus enabling thee-commerce platform 100 to provide shipping service functionalitywithout directly impacting code running in the core commerce facility136.

Many merchant problems may be solved by letting partners improve andextend merchant workflows through application development, such asproblems associated with back-office operations (merchant-facingapplications) and in the storefront (customer-facing applications). As apart of doing business, many merchants will use mobile and web relatedapplications on a daily basis for back-office tasks (e.g.,merchandising, inventory, discounts, fulfillment, and the like) andstorefront tasks (e.g., applications related to their online shop, forflash-sales, new product offerings, and the like), where applications142, through extension/API 140, help make products easy to view andpurchase in a fast growing marketplace. In various embodiments,partners, application developers, internal applications facilities, andthe like, may be provided with a software development kit (SDK), such asthrough creating a frame within the administrator 114 that sandboxes anapplication interface. In various embodiments, the administrator 114 maynot have control over nor be aware of what happens within the frame. TheSDK may be used in conjunction with a user interface kit to produceinterfaces that mimic the look and feel of the e-commerce platform 100,such as acting as an extension of the core commerce facility 136.

Applications 142 that utilize APIs may pull data on demand, but oftenthey also need to have data pushed when updates occur. Update events maybe implemented in a subscription model, such as for example, customercreation, product changes, or order cancelation. Update events mayprovide merchants with needed updates with respect to a changed state ofthe core commerce facility 136, such as for synchronizing a localdatabase, notifying an external integration partner, and the like.Update events may enable this functionality without having to poll thecore commerce facility 136 all the time to check for updates, such asthrough an update event subscription. In various embodiments, when achange related to an update event subscription occurs, the core commercefacility 136 may post a request, such as to a predefined callback URL.The body of this request may contain a new state of the object and adescription of the action or event. Update event subscriptions may becreated manually, in the administrator facility 114, or automatically(e.g., via the API). In various embodiments, update events may be queuedand processed asynchronously from a state change that triggered them,which may produce an update event notification that is not distributedin real-time.

Reference is made to FIG. 3, which is another depiction of thee-commerce platform 100. FIG. 3 omits some details that have beendescribed with reference to FIG. 1, and shows further details discussedbelow. In various embodiments, the e-commerce platform 100 may provideapplication development support 128. Application development support 128may include developer products and tools 202 to aid in the developmentof applications, an application dashboard 204 (e.g., to providedevelopers with a development interface, to administrators formanagement of applications, to merchants for customization ofapplications, and the like), facilities for installing and providingpermissions 206 with respect to providing access to an application 142(e.g., for public access, such as where criteria must be met beforebeing installed, or for private use by a merchant), applicationsearching 208 to make it easy for a merchant to search for applications142 that satisfy a need for their storefront 139, applicationrecommendations 210 to provide merchants with suggestions on how theycan improve the user experience through their storefront 139, adescription of core application capabilities 214 within the corecommerce facility 136, and the like. These support facilities may beutilized by application development 108 performed by any entity,including the merchant developing their own application 142, athird-party developer developing an application 142 (e.g., contracted bya merchant, developed on their own to offer to the public, contractedfor use in association with the e-commerce platform 100, and the like),or an application being developed by internal personal resourcesassociated with the e-commerce platform 100. In various embodiments,applications 142 may be assigned an application identifier (ID), such asfor linking to an application (e.g., through an API), searching for anapplication, making application recommendations, and the like.

The core commerce facility 136 may include base functions of thee-commerce platform 100 and expose these functions through APIs toapplications 142. The APIs may enable different types of applicationsbuilt through application development 108. Applications 142 may becapable of satisfying a great variety of needs for merchants but may begrouped roughly into three categories: customer-facing applications 216,merchant-facing applications 218, or integration applications 220.Customer-facing applications 216 may include storefront 139 or channels110 that are places where merchants can list products and have thempurchased (e.g., the online store, applications for flash sales (e.g.,merchant products or from opportunistic sales opportunities fromthird-party sources), a mobile store application, a social mediachannel, an application for providing wholesale purchasing, and thelike). Merchant-facing applications 218 may include applications thatallow the merchant to administer their storefront 139 (e.g., throughapplications related to the web or website or to mobile devices), runtheir business (e.g., through applications related to POS devices 152),to grow their business (e.g., through applications related to shipping(e.g., drop shipping), use of automated agents, use of process flowdevelopment and improvements), and the like. Integration applications220 may include applications that provide useful integrations thatparticipate in the running of a business, such as shipping providers 112and payment gateways.

In various embodiments, an application developer may use an applicationproxy to fetch data from an outside location and display it on the pageof an online storefront 139. Content on these proxy pages may bedynamic, capable of being updated, and the like. Application proxies maybe useful for displaying image galleries, statistics, custom forms, andother kinds of dynamic content. The core-application structure of thee-commerce platform 100 may allow for an increasing number of merchantexperiences to be built in applications 142 so that the core commercefacility 136 can remain focused on the more commonly utilized businesslogic of commerce.

The e-commerce platform 100 provides an online shopping experiencethrough a curated system architecture that enables merchants to connectwith customers in a flexible and transparent manner. A typical customerexperience may be better understood through an embodiment examplepurchase workflow, where the customer browses the merchant's products ona channel 110, adds what they intend to buy to their cart, proceeds tocheckout, and pays for the content of their cart resulting in thecreation of an order for the merchant. The merchant may then view andfulfill (or cancel) the order. The product is then delivered to thecustomer. If the customer is not satisfied, they might return theproducts to the merchant.

In an example embodiment, a customer may browse a merchant's products ona channel 110. A channel 110 is a place where customers can view and buyproducts. In various embodiments, channels 110 may be modeled asapplications 142 (a possible exception being the online store 138, whichis integrated within the core commence facility 136). A merchandisingcomponent may allow merchants to describe what they want to sell andwhere they sell it. The association between a product and a channel maybe modeled as a product publication and accessed by channelapplications, such as via a product listing API. A product may have manyoptions, like size and color, and many variants that expand theavailable options into specific combinations of all the options, likethe variant that is extra-small and green, or the variant that is sizelarge and blue. Products may have at least one variant (e.g., a “defaultvariant” is created for a product without any options). To facilitatebrowsing and management, products may be grouped into collections,provided product identifiers (e.g., stock keeping unit (SKU)) and thelike. Collections of products may be built by either manuallycategorizing products into one (e.g., a custom collection), by buildingrulesets for automatic classification (e.g., a smart collection), andthe like. Products may be viewed as 2D images, 3D images, rotating viewimages, through a virtual or augmented reality interface, and the like.

In various embodiments, the customer may add what they intend to buy totheir cart (in an alternate embodiment, a product may be purchaseddirectly, such as through a buy button as described herein). Customersmay add product variants to their shopping cart. The shopping cart modelmay be channel specific. The online store 138 cart may be composed ofmultiple cart line items, where each cart line item tracks the quantityfor a product variant. Merchants may use cart scripts to offer specialpromotions to customers based on the content of their cart. Since addinga product to a cart does not imply any commitment from the customer orthe merchant, and the expected lifespan of a cart may be in the order ofminutes (not days), carts may be persisted to an ephemeral data store.

The customer then proceeds to checkout. A checkout component mayimplement a web checkout as a customer-facing order creation process. Acheckout API may be provided as a computer-facing order creation processused by some channel applications to create orders on behalf ofcustomers (e.g., for point of sale). Checkouts may be created from acart and record a customer's information such as email address, billing,and shipping details. On checkout, the merchant commits to pricing. Ifthe customer inputs their contact information but does not proceed topayment, the e-commerce platform 100 may provide an opportunity tore-engage the customer (e.g., in an abandoned checkout feature). Forthose reasons, checkouts can have much longer lifespans than carts(hours or even days) and are therefore persisted. Checkouts maycalculate taxes and shipping costs based on the customer's shippingaddress. Checkout may delegate the calculation of taxes to a taxcomponent and the calculation of shipping costs to a delivery component.A pricing component may enable merchants to create discount codes (e.g.,“secret” strings that when entered on the checkout apply new prices tothe items in the checkout). Discounts may be used by merchants toattract customers and assess the performance of marketing campaigns.Discounts and other custom price systems may be implemented on top ofthe same platform piece, such as through price rules (e.g., a set ofprerequisites that when met imply a set of entitlements). For instance,prerequisites may be items such as “the order subtotal is greater than$100” or “the shipping cost is under $10”, and entitlements may be itemssuch as “a 20% discount on the whole order” or “$10 off products X, Y,and z”.

Customers then pay for the content of their cart resulting in thecreation of an order for the merchant. Channels 110 may use the corecommerce facility 136 to move money, currency or a store of value (suchas dollars or a cryptocurrency) to and from customers and merchants.Communication with the various payment providers (e.g., online paymentsystems, mobile payment systems, digital wallet, credit card gateways,and the like) may be implemented within a payment processing component.The actual interactions with the payment gateways 106 may be providedthrough the card server environment 148. In various embodiments, thepayment gateway 106 may accept international payment, such asintegrating with leading international credit card processors. The cardserver environment 148 may include a card server application, card sink,hosted fields, and the like. This environment may act as the securegatekeeper of the sensitive credit card information.

FIG. 4 presents, in a non-limiting example, a simplified sequencediagram of the interactions between the core commerce facility 136 andthe card server environment 148 during payment processing of a credit,prepaid, gift or other card on a Web Checkout.

In various embodiments, most of the process may be orchestrated by apayment processing job. The core commerce facility 136 may support manyother payment methods, such as through an offsite payment gateway 106(e.g., where the customer is redirected to another website), manually(e.g., cash), online payment methods (e.g., online payment systems,mobile payment systems, digital wallet, credit card gateways, and thelike), gift cards, and the like. At the end of the checkout process, anorder is created. An order is a contract of sale between the merchantand the customer where the merchant agrees to provide the goods andservices listed on the orders (e.g., order line items, shipping lineitems, and the like) and the customer agrees to provide payment(including taxes). This process may be modeled in a sales component.Channels 110 that do not rely on core commerce facility checkouts mayuse an order API to create orders. Once an order is created, an orderconfirmation notification may be sent to the customer and an orderplaced notification sent to the merchant via a notifications component.Inventory may be reserved when a payment processing job starts to avoidover-selling (e.g., merchants may control this behavior from theinventory policy of each variant). Inventory reservation may have ashort time span (minutes) and may need to be very fast and scalable tosupport flash sales (e.g., a discount or promotion offered for a shorttime, such as tailored towards impulse buying). The reservation isreleased if the payment fails. When the payment succeeds, and an orderis created, the reservation is converted into a long-term inventorycommitment allocated to a specific location. An inventory component mayrecord where variants are stocked, and tracks quantities for variantsthat have inventory tracking enabled. It may decouple product variants(a customer facing concept representing the template of a productlisting) from inventory items (a merchant facing concept that representan item whose quantity and location is managed). An inventory levelcomponent may keep track of quantities that are available for sale,committed to an order or incoming from an inventory transfer component(e.g., from a vendor). The merchant may then view and fulfill (orcancel) the order.

An order assessment component may implement a business process merchantsuse to ensure orders are suitable for fulfillment before actuallyfulfilling them. Orders may be fraudulent, require verification (e.g.,ID checking), have a payment method which requires the merchant to waitto make sure they will receive their funds, and the like. Risks andrecommendations may be persisted in an order risk model. Order risks maybe generated from a fraud detection tool, submitted by a third-partythrough an order risk API, and the like. Before proceeding tofulfillment, the merchant may need to capture the payment information(e.g., credit card information) or wait to receive it (e.g., via a banktransfer, check, and the like) and mark the order as paid. The merchantmay now prepare the products for delivery. In various embodiments, thisbusiness process may be implemented by a fulfillment component. Thefulfillment component may group the line items of the order into alogical fulfillment unit of work based on an inventory location andfulfillment service. The merchant may assess the order, adjust the unitof work, and trigger the relevant fulfillment services, such as througha manual fulfillment service (e.g., at merchant managed locations) usedwhen the merchant picks and packs the products in a box, purchase ashipping label and input its tracking number, or just mark the item asfulfilled. A custom fulfillment service may send an email (e.g., alocation that does not provide an API connection). An API fulfillmentservice may trigger a third party, where the third-party applicationcreates a fulfillment record. A legacy fulfillment service may trigger acustom API call from the core commerce facility 136 to a third party(e.g., fulfillment by Amazon). A gift card fulfillment service mayprovision (e.g., generating a number) and activate a gift card.Merchants may use an order printer application to print packing slips.The fulfillment process may be executed when the items are packed in thebox and ready for shipping, shipped, tracked, delivered, verified asreceived by the customer, and the like.

If the customer is not satisfied, they may be able to return theproduct(s) to the merchant. The business process merchants may gothrough to “un-sell” an item may be implemented by a returns component.Returns may consist of a variety of different actions, such as arestock, where the product that was sold actually comes back into thebusiness and is sellable again; a refund, where the money that wascollected from the customer is partially or fully returned; anaccounting adjustment noting how much money was refunded (e.g.,including if there was any restocking fees, or goods that were notreturned and remain in the customer's hands); and the like. A return mayrepresent a change to the contract of sale (e.g., the order), and wherethe e-commerce platform 100 may make the merchant aware of complianceissues with respect to legal obligations (e.g., with respect to taxes).In various embodiments, the e-commerce platform 100 may enable merchantsto keep track of changes to the contract of sales over time, such asimplemented through a sales model component (e.g., an append-onlydate-based ledger that records sale-related events that happened to anitem).

FIG. 5 is a block diagram of an example hardware configuration of thee-commerce platform 100. It should be noted that different components ofthe e-commerce platform 100 (e.g., the data facility 134, analyticsfacility 132, core commerce facility 136 and applications 142) may beimplemented in separate hardware or software components, on a commonhardware component or server or configured as a common (integrated)service or engine in the e-commerce platform 100. In the example of FIG.5, the e-commerce platform 100 includes a core server 510, a data server520 and an applications server 530, which are each in communication witheach other (e.g., via wired connections and/or via wireless intranetconnections). Each of the servers 510, 520, 530 include a respectiveprocessing device 512, 522, 532 (each of which may be, for example, amicroprocessor, graphical processing unit, digital signal processor orother computational element), a respective memory 514, 524, 534 (each ofwhich may be, for example, random access memory (RAM), read only memory(ROM), hard disk, optical disc, subscriber identity module (SIM) card,memory stick, secure digital (SD) memory card, and the like, and mayinclude tangible or transient memory), and a respective communicationsinterface 516, 526, 536 (each of which may include transmitter, receiverand/or transceiver for wired and/or wireless communications). The coreserver 510 may store instructions and perform operations relevant tocore capabilities of the e-commerce platform, such as providing theadministrator 114, analytics 132, core commerce facility 136, services116 and/or financial facility 130, among others. The data server 520 maybe used to implement the data facility 134, among others. Theapplications server 530 may store instructions and perform operationsrelevant to the applications 142, such as storing instructions and datafor the applications 142 and for implementing application developmentsupport 128.

Merchants and customers, using respective devices 102, 150, 152 mayaccess the e-commerce platform 100 via one or more networks 540 (e.g.,wired and/or wireless networks, including a virtual private network(VPN), the Internet, and the like).

Although FIG. 5 illustrates an example hardware implementation of thee-commerce platform 100, it should be understood that otherimplementations may be possible. For example, there may be greater orfewer numbers of servers, the e-commerce platform 100 may be implementedin a distributed manner, or at least some of the memories 514, 524, 534may be replaced with external storage or cloud-based storage, amongother possible modifications.

FIG. 6 is another depiction of the e-commerce platform 100 that omitssome details that have been described with reference to FIG. 1, andshows further details discussed below. In particular, FIG. 6 illustratessome details of the e-commerce platform 100 that are relevant togenerating and managing a messaging campaign.

In the context of a messaging campaign, a customer of the e-commerceplatform 100 may also be a recipient who is an intended recipient of adirected messaging campaign. Accordingly, FIG. 6 illustrates thecustomer as a customer/recipient, and the customer/recipient mayinteract with the e-commerce platform 100 via the customer/recipientdevice 150. However, it should be understood that not all customers ofthe e-commerce platform 100 may be a recipient of a messaging campaign,and not all recipients of a messaging campaign may be a customer of thee-commerce platform 100. For generality, the present disclosure willrefer to “recipients” of a directed messaging campaign. In cases where arecipient is not a current customer of the e-commerce platform 100, thee-commerce platform 100 may nonetheless obtain at least generalizedinformation about the online behavior of the non-customer recipient, forexample via anonymized statistical data and/or via user-consentedsharing of information with a social media platform, among otherpossibilities.

In the context of a messaging campaign, a merchant on the e-commerceplatform 100 may also be a marketer who is planning a messagingcampaign. Accordingly, FIG. 6 illustrates the merchant as amerchant/marketer, and the merchant/marketer may interact with thee-commerce platform via the merchant/marketer device 102. Additionally,a marketer (who is not also a merchant on the e-commerce platform 100)may interact with the e-commerce platform 100 via a marketer device 103.Such a marketer may, for example, use certain services provided by thee-commerce platform 100, such as for generating a messaging campaign asdiscussed below, without having to be a customer or merchant who issubscribed to the e-commerce platform 100. In some examples, thee-commerce platform 100 may make certain services/applications, such asthe messaging campaign engine discussed below, accessible to users asstandalone services/applications.

The analytics facility 132 in this example includes an engagementanalyzer 342, which may be implemented as a sub-module of the analyticsfacility 132 or may be implemented as part of the general functions ofthe analytics facility 132. As will be discussed further below, theengagement analyzer 342 serves to analyze online behavior of customers,in order to determine (a level of) engagement of customers with certaindistribution channels, certain online stores and/or certain messages,among other possibilities. In some examples, some or all functions ofthe engagement analyzer 342 may be implemented using a machine-learningsystem.

The e-commerce platform 100 in this example includes a messagingcampaign engine 350. The messaging campaign engine 350 may be part ofthe applications 142 or services 116 of the e-commerce platform 100 forexample, or may be a standalone component of the e-commerce platform100. The messaging campaign engine 350 may, for example, be implementedby the applications server 530 of FIG. 5. The messaging campaign engine350 in this example includes a campaign generator 354 sub-module. Thecampaign generator 354 enables automatic generation of recommendedparameters for a messaging campaign, as will be discussed further below.The messaging campaign engine 350 may communicate with the communicationfacility 129 or another communications interface of the e-commerceplatform 100 to enable distribution of messages in accordance with adefined campaign. The messaging campaign engine 350 in this example alsostores messaging campaign-related data, such as default campaignparameters 352, defined campaign parameters 356 and engagement metrics358. The engagement metrics 358 may be provided to the messagingcampaign engine 350 by the analytics facility 132. In some examples,some or all of the messaging campaign-related data, such as defaultcampaign parameters 352, defined campaign parameters 356 and engagementmetrics 358, may be stored outside of the messaging campaign engine 350,for example in the data facility 134 (see FIG. 1).

A merchant or marketer may engage with the messaging campaign engine 350to plan and implement a messaging campaign. For simplicity, thefollowing discussion will refer to a merchant engaging with themessaging campaign engine 350; however it should be understood that thefollowing discussion may be similarly applicable in the case of anon-merchant marketer instead of a merchant/marketer.

A merchant may submit a proposed messaging campaign via the merchantdevice 102, using a user interface (e.g., an online portal) provided bythe e-commerce platform 100. A proposed messaging campaign may besubmitted by, for example, selecting from available campaign templatesthat may be populated using the default campaign parameters 352. Aproposed messaging campaign may be submitted by only selecting a subsetof the required campaign parameters (e.g., submitting only the messagecontent), and the messaging campaign engine 350 may use default campaignparameters 352 to populate the remaining required campaign parameters.

In some examples, the merchant may not be required to submit anycampaign parameters at all. Instead, the e-commerce platform 100 may useinformation already available (via the e-commerce platform 100'sanalytics facility 132 for example) about the merchant's online store138 to automatically generate a proposed messaging campaign. Forexample, the messaging campaign engine 350 may automatically generate aproposed set of campaign parameters for a messaging campaign, based oninformation about the type of offering, number of sales, inventory size,etc. of the merchant's online store 138 on the e-commerce platform 100.

A messaging campaign, in the present disclosure, may be a planned set ofmessages (which may be marketing messages, in which case the messagingcampaign may also be referred to as a marketing campaign) that iscommunicated to certain intended recipients. In the present disclosure,a messaging campaign (and in particular a marketing campaign) may beassociated with an online store (e.g., the online store 138 of thee-commerce platform 100, or an online store that is not part of thee-commerce platform 100) and/or an online merchant.

A messaging campaign may be defined by a set of campaign parameters,such as: number of phases of the campaign, number of different messages,a schedule for sending out messages (which may be defined in absoluteterms (e.g., specific date(s) and/or time(s)), relative terms (e.g.,interval of days between phases of the campaign), conditional terms(e.g., conditional on an intended recipient clicking on a link), etc.),content(s) of messages (which may or may not include an incentive, suchas a coupon or discount), intended recipients (which may be defined asindividuals, groups, demographics, etc.), distribution channel(s) (e.g.,email, text message, social network message, etc.), among other possibleparameters.

A messaging campaign may be conducted over multiple phases. For example,a campaign may be divided into multiple phases based on the schedule.Multiple messages may be directed towards a given recipient over themultiple phases of the campaign. For example, a first phase maycommunicate an initial first message to the given recipient, thenaccording to the schedule a second message (which may have the samecontent or different content from the first message) may be communicatedagain to the same given recipient in a second phase of the campaign.

The messaging campaign engine 350 may store default parameters 352,which may be predefined (e.g., by the e-commerce platform 100). Thedefault parameters 352 are messaging campaign parameters that may beused to generate and carry out a messaging campaign when one or morerequired parameters have not been submitted by a merchant. In someexamples, the default parameters 352 may be general to all merchantsusing the services of the messaging campaign engine 350. In someexamples, there may be some level of specificity in the defaultparameters 352, for example there may be different sets of defaultparameters 352 depending on the size (e.g., as measured by the amount ofyearly sales) of the merchant.

A merchant using the services of the messaging campaign engine 350 mayalso submit (e.g., via a user interface, such as an online portalprovided by the e-commerce platform 100, which may be accessible via amerchant device 102 or marketer device 103) one or more user-submittedparameters for a messaging campaign. The user-submitted parameter(s) maybe supplemented by one or more default parameters 352 as appropriate. Insome examples, instead of submitting any user-submitted parameters, amerchant may select to use the default parameters 352.

The messaging campaign engine 350 uses the campaign generator 354 togenerate a set of parameters for a messaging campaign. For example, thecampaign generator 354 may determine that a set of user-submittedparameters should be supplemented by one or more default parameters 352(e.g., the merchant has not submitted intended recipients, so thecampaign generator 354 identifies a default intended demographic fromthe default parameters 352 and adds this as a parameter for themessaging campaign). As will be discussed further below, the campaigngenerator 354 may generate recommended parameters for a messagingcampaign, such as recommended distribution channel(s) for certain groups(or subgroups) of intended recipients. The campaign generator 354 maygenerate recommended parameters prior to the start of a messagingcampaign, as well as dynamically during the life of the messagingcampaign (e.g., generating new recommended parameters for differentphases of a campaign). Any recommended parameter(s) generated by thecampaign generator 354 may be notified to a merchant, who may be offeredan option to accept or reject the recommended parameter(s).

After a set of campaign parameters have been approved by the merchant(e.g., via the user interface provided by the e-commerce platform 100),including any recommended parameter(s) that have been offered formerchant approval, the approved parameters may be stored in the definedcampaign parameters 356 of the messaging campaign engine 350. Themessaging campaign engine 350 may store multiple sets of definedcampaign parameters 356, corresponding to respective multiple messagingcampaigns. The defined campaign parameters 356 stored by the messagingcampaign engine 350 may be limited to active or ongoing messagingcampaigns, or may also include historical or completed messagingcampaigns.

The messaging campaign engine 350 uses the set of defined campaignparameters 356 to generate messages with the defined message content(s),addressed to the defined intended recipient(s), to be sent over thedefined distribution channel(s), and according to the defined schedule.In some examples, the messaging campaign engine 350 may make use ofmessage templates (which may be stored as default parameters 352) tocreate message content(s). In some examples, the messaging campaignengine 350 may extract or otherwise obtain information (e.g., contactinformation for individual intended recipients) from the data facility134 or other database in order to generate the messages. For example,the messaging campaign engine 350 may use customer information stored inthe data facility 134 to identify individuals that belong in the groupof intended recipients (e.g., a defined demographic, such as a definedage group) defined for a messaging campaign, and generate messages tothose individuals using contact information stored in the data facility134. For privacy and security purposes, the messaging campaign engine350 may limit the customer information extracted for a particularmerchant campaign to information collected with consent (e.g., by theparticular merchant and/or the platform 100) and not make such extractedinformation available to other merchants or third parties. The messagingcampaign engine 350 may then provide the generated messages to thecommunications facility 129, which in turn transmits the messages to theintended recipient(s) over the defined distribution channel(s).

The engagement analyzer 342 analyzes recipients' engagement with amessaging campaign. The engagement analyzer 342 may analyze engagementover the entire schedule of a messaging campaign, and may also analyzeengagement for a defined period of time (e.g., one month) after the endof a messaging campaign. The engagement analyzer 342 may analyzerecipients' engagement in an individualized manner and/or in ageneralized (e.g., aggregated or statistical) manner. For example, if anindividual recipient gives permission to access individualizedinformation, the engagement analyzer 342 may analyze how that individualrecipient responds (e.g., open or delete a message, click on a link in amessage, etc.) to each phase of a given messaging campaign. In anotherexample, the engagement analyzer 342 may analyze engagement in ageneralized manner, for example by calculating statistics on thepercentage of messages that were read in each phase of a given messagingcampaign. Various suitable techniques may be used for individualized orgeneralized analysis of engagement.

The engagement analyzer 342 may generate engagement metrics for a givenmessaging campaign. The engagement metrics may be individualized and/orgeneralized, depending on the type of analysis carried out. Theengagement metrics may be a quantitative representation of the degree towhich intended recipient(s) engage with the given messaging campaign.Output generated by the engagement analyzer 342 may be stored by themessaging campaign engine 350 as engagement metrics 358. The engagementmetrics 358 may be stored in association with information identifyingthe corresponding messaging campaign. In some examples, the engagementmetrics 358 may be stored in association with information about certainparameters of the messaging campaign. Such detailed information mayenable the messaging campaign engine 350 to determine (e.g., using apredictive algorithm or using a machine-learning system) which campaignparameters are more likely to result in positive engagement fromintended recipients. For example, a response likelihood matrix or otherstatistics-based analytics may be generated to learn typical recipientresponses, based on multiple historical campaigns.

In some examples, the engagement metrics 358 may be stored inassociation with information identifying an individual recipient or ageneralized recipient group (e.g., demographic group). Engagementmetrics 358 may be updated over the life of a messaging campaign (e.g.,as recipients are messaged over multiple phases of the campaign). Insome examples, engagement metrics 358 may be updated over multiplemessaging campaigns (e.g., if a merchant conducts multiple messagingcampaigns over time).

In an example, engagement metrics 358 may be a score between 0 to 5,with 0 indicating most negative engagement (e.g., recipient deletedmessage or unsubscribed from future messages), 2 indicatingnon-engagement (e.g., recipient did not open message or recipient is anew intended recipient), and 5 indicating most positive engagement(e.g., recipient made a purchase after receiving message).

In some examples, as discussed further below, a recipient's engagementwith the messaging campaign may be evaluated based on analysis of therecipient's online activity. The online activity may be online activitythat is associated with a store (which may or may not be the onlinestore for which the messaging campaign is being generated). Onlineactivity may include, for example, a page view event, an offeringselection event, a purchase transaction event, a product search event,an offering return event, a page share event (e.g., sharing over asocial network or other online channel), a virtual shopping cart event(e.g., an addition of an offering to the virtual shopping cart, orremoval of an offering from the virtual shopping cart), a purchaseabandonment event (e.g., starting a purchase transaction (e.g.,beginning checkout of virtual shopping cart) without completing thepurchase transaction), and/or a product review event, among otherpossibilities.

A recipient's online activity may be considered to be relevant to amessaging campaign without there being a direct correlation with themessaging campaign. For example, online activity that takes place during(or shortly after) a given messaging campaign may be the purchase of anoffering that is related to (e.g., in the same category) the offeringpromoted in the given messaging campaign, which may affect how therecipient would respond or engage with the given messaging campaign.This may be taken into account in the engagement metrics 358. Forexample, online activity related to a given store (e.g., a page view ofa store's website) that occurs subsequent to a messaging campaign forthat given store may be considered a positive engagement for themessaging campaign (a causal relationship need not be established). Theonline activity may also be related to one or more campaign parameters.For example, a page view of a store's website may be a positiveengagement with a message sent via a certain distribution channel (e.g.,email).

FIG. 7 is a flowchart illustrating an example method 700 for generatinga messaging campaign associated with an online store. The method 700 maybe implemented by the e-commerce platform 100 (e.g., using the messagingcampaign engine 350 and/or the analytics facility 132). The method 700may be implemented by a processing device executing instructions (e.g.,at the core server 510 or the applications server 530).

Optionally, at 702, a set of proposed campaign parameters is received.The set of proposed campaign parameters may be user-submittedparameters, for example received from a merchant or marketer via anonline user interface provided by the e-commerce platform 100.

At 704, a set of proposed intended recipients for the proposed messagingcampaign is identified. The intended recipients may be identified fromthe proposed campaign parameters received at 702. Alternatively, theintended recipients may be identified based on default parameters. Forexample, the campaign generator 354 may receive identification of a setof intended recipients from the default parameters 352, if nouser-submitted intended recipients was provided. The set of intendedrecipients may be identified by recipient identifier (e.g., customerprofile ID), recipient contact information (e.g., email address, phonenumber), demographic group (e.g., certain characteristics such as age,gender, geographical location, etc.), among other possibilities.

At 706, one or more recommended campaign parameters are determined.Determining recommended campaign parameter(s) includes steps 708 and 716described below.

At 708, one or more intended recipient groups are identified from theset of intended recipients. Intended recipient groups (also referred tosimply as groups or recipient groups) are generally non-overlappinggroups, each having one or more intended recipients. Recipient groupsare identified from the set of intended recipients based on variousoptional criteria, such as: based on recipients' online activity (at710); based on recipients' characteristics (at 712); and/or byidentifying additional recipient(s) to be included (At 714). Suchcriteria may be used in combination for identifying groups of intendedrecipients.

Generally, the groups identified at 708 are non-overlapping groups,meaning that there is no intended recipient common between twoidentified groups. This may help to avoid overlapping sub-campaigns, sothat an intended recipient is not overwhelmed with the same message frommultiple distribution channels. In other examples, it may be useful toallow overlapping groups at 708, meaning that there may be intendedrecipient(s) common between two or more identified groups. Overlappinggroups may be useful in situations where it would be desirable tomessage the same intended recipient over multiple distribution channels,possibly with different messages being sent over different distributionchannels, to increase exposure.

For example, optionally at 710, a group may be identified based ononline activity associated with member(s) of that group. The onlineactivity may be online activity that is associated with a store (whichmay or may not be the online store for which the messaging campaign isbeing generated). Online activity may include, for example, a page viewevent, an offering selection event, a purchase transaction event, aproduct search event, an offering return event, a page share event(e.g., sharing over a social network or other online channel), a virtualshopping cart event (e.g., an addition of an offering to the virtualshopping cart, or removal of an offering from the virtual shoppingcart), a purchase abandonment event (e.g., starting a purchasetransaction (e.g., beginning checkout of virtual shopping cart) withoutcompleting the purchase transaction), and/or a product review event. Theonline activity may also be online activity and/or events associatedwith previous messaging campaigns.

Online activity of potential intended recipients may be determined bythe analytics facility 132, prior to or at the time of performing themethod 700. For example, the analytics facility 132 may have access toinformation about how customers of the e-commerce platform 100 interactwith online stores 138 hosted by the e-commerce platform 100, includingevents indicative of which customer has viewed, selected, purchased,searched, returned, or reviewed a given offering of a given online store138, for example. In some examples, online activity of potentialintended recipients may be alternatively or additionally determined by asystem external to the e-commerce platform 100 and provided to thee-commerce platform 100. For example, the e-commerce platform 100 mayhave an agreement with an external system (e.g., a social mediaplatform, an external retail platform, an online search platform, etc.)to obtain event information or other analytics (which may be anonymizedor generalized for privacy reasons) indicative of online behavior ofcertain individuals or demographics.

The campaign generator 354 may cross-reference such analytics with theproposed intended recipients to identify groups among the intendedrecipients. For example, analytics (whether from the analytics facility132 of the e-commerce platform 100 or from an external system) mayindicate that certain individuals have recently (e.g., within the pastmonth) purchased something from the online store for which the messagingcampaign is being generated. Those individuals may be identified as onegroup, and individuals who have not purchased from the online storerecently may be identified as another group.

In some cases, an intended recipient may use different identifiers fordifferent online activity. For example, an intended recipient may haveone identifier for social media activity, and a different identifierrelated to online purchases. The analytics facility 132 may determinethat the two different identifiers are in fact related to the sameintended recipient, for example by cross-referencing the differentidentifiers with some common information (e.g., a common shippingaddress) that is known (e.g., from customer profile information storedon the e-commerce platform 100).

The analysis of online activity may be anonymized and/or categorized bygroup characteristics (e.g., age, geographical region, family status,etc.). In some examples, the analysis of online activity may begeneralized across multiple stores. When generalized across multiplestores, the online activity can be further categorized or segmented bystore type, store size, relevant industry, offering category, etc.

Information extracted from such analysis may be maintained internal tothe e-commerce platform 100 and may not be shared with merchants,customers, or external users (e.g., in order to ensure privacy andsecurity). In some examples, information from such analysis may beextracted using a machine-learning system. If a machine-learning systemis used, the extraction of analytics may be performed in a hidden layerof the machine-learning system (i.e., not part of the output provided bythe machine-learning system), such that such analytics is not explicitlyexposed even within the e-commerce platform 100.

In another example, optionally at 712, a group may be identified basedon characteristics of member(s) of that group. Characteristics mayinclude non-behavioral characteristics, such as demographiccharacteristics. For example, characteristics that may be used toidentify a group include age, income, gender, geographical location,family status, among other possibilities.

Characteristics of potential intended recipients may be determined basedon information stored in the data facility 134 (e.g., customer profileinformation). For example, individual intended recipients may becross-referenced with their customer profiles based on their contactinformation. In some examples, the parameters defining intendedrecipients may define the intended recipients in terms of theircharacteristics (e.g., based on a certain demographic), in which caseinformation from the data facility 134 may be used to identifyindividuals that fit the desired demographic. From those identifiedindividuals, further characteristics may be determined, which may beused to divide the desired demographic into separate recipient groups.Alternatively or additionally, groups may be divided out from a defineddesired demographic, based on known statistics about that demographic.For example, a campaign parameter may specify that the campaign is to bedirected towards the age group 19-29. The campaign generator 354 mayfurther identify, from that demographic, a group of intended recipientshaving incomes below $50,000 and another group having incomes above$50,000.

In another example, optionally at 716, one or more additional recipientsmay be identified, who were not included in the set of intendedrecipients identified at 704.

For example, the campaign generator 354 may identify potential intendedrecipient(s) excluded from the initial set of intended recipients (e.g.,initial set of intended recipients is only males aged 19-29, and thecampaign generator 354 may identify females aged 19-29 as additionalintended recipients). This may be based on analytics (e.g., from theanalytics facility 132) indicating that purchasing habits of theinitially excluded recipient(s) is similar to the purchasing habits ofthe initially identified intended recipients.

In another example, the campaign generator 354 may identify a group ofintended recipients that is partly within the initially identifiedintended recipients (e.g., initial set of intended recipients is onlyuniversity students, and the campaign generator 354 may identify allthose aged 19-29 as additional intended recipients).

After identifying one or more groups, at 716, a recommended distributionchannel is determined for each group. A distribution channel for amessage in the messaging campaign may be a message over a social networkservice, a message over an email service, a message over a messagingservice in a merchant app, or a message over a text or other (e.g.,direct) messaging service, among other possibilities. Differentdistribution channels may be recommended for different (non-overlapping)recipient groups. For example, a first distribution channel (e.g.,email) may be recommended for a first group, and a different seconddistribution channel (e.g., social media) may be recommended for asecond non-overlapping group.

For example, the campaign generator 354 may determine that a group thathas purchased an offering from the online store is more likely to havepositive engagement with a message sent via email hence emaildistribution to that group is recommended; or that an age group 30-49 ismore likely to have positive engagement with a message sent via directtext messaging. This may be determined based on a predefined rule, orbased on behavior patterns determined via machine-learning, and/or basedon historical engagement. The recommended distribution channel may bedetermined based on information derived from one or more other messagingcampaigns conducted for the same or different online store. For example,information from the engagement metrics 358 may be used to determine(e.g., by training a machine-learning system on the historical campaignsand associated engagement metrics 358) how different recipient groupspositively or negatively engage with various messaging campaigns havingdifferent campaign parameters.

For example, the campaign generator 354 may determine that positiveonline activity (e.g., events indicative of an online purchase) in agiven group is correlated with a prior message delivered via aparticular distribution channel (e.g., email), and hence recommend thesame distribution channel again for that given group.

In addition or alternative to determining a recommended distributionchannel for each group, the campaign generator 354 may generate otherrecommended parameters, such as: a recommended campaign schedule for atleast one group; a recommended message content for at least one group; arecommended number of messages or campaign phases for at least onegroup; or a recommended incentive to be included in a message for atleast one group, among other possibilities. It should be understood thatparameters may be recommended in combination. For example, a first setof recommended parameters for a first group may include both a firstdistribution channel (e.g., email) and a first schedule (e.g., messagessent on a monthly basis), and a second set of recommended parameters fora second group may include both a second distribution channel (e.g.,social media) and a second schedule (e.g., messages sent on a weeklybasis).

At 718, a recommendation is generated including the recommended campaignparameters. The recommendation includes indication of the identifiedgroup(s) and the respective recommended parameter(s) (e.g., recommendeddistribution channel) for each group. If additional recipient(s) havebeen identified at 714, the recommendation may include an indication(e.g., a general indication of the demographic or characteristics) ofthe additional recipient(s).

For privacy reasons, the recommendation that is provided to the merchantor marketer may omit identifying information about individualrecipients. For example, if the recommended campaign parameter hasidentified individuals A, B and C belonging to group X and thatdistribution channel Y should be used to direct messages towards groupX, the merchant or marketer may only be notified that it is recommendedto direct messages to “some” recipients via distribution channel Y.

In some examples, the recommendation may be provided to the merchant ormarketer in the form of a notification (e.g., via the user interface),and may offer an option to accept or reject the recommendation. If theoption to accept or reject is provided, the recommendation may alsoinclude a predicted success rate or historical success rate associatedwith certain recommended parameter(s) to motivate the merchant ormarketer to accept the recommended parameter(s). In other examples, therecommendation may be automatically implemented without providing anoption to reject the recommendation. In some examples, therecommendation may not be explicitly provided to the merchant ormarketer, and may be automatically implemented without explicitnotification to the merchant or marketer.

Optionally, at 720, if an option to accept or reject the recommendationwas provided, a confirmation or modification of campaign parameters maybe received (e.g., via a user interface).

At 722, the messaging campaign is conducted (e.g. campaign messages aresent to the intended recipients) using the campaign parameters. In someexamples, the messaging campaign is conducted by the messaging campaignengine 350. In other examples, the messaging campaign engine 350 mayoutput the campaign parameters to enable the messaging campaign to beconducted by an external system. For example, a marketer may use themessaging campaign engine 350, as a service provided by the e-commerceplatform 100 (or as a stand-alone service provided externally to thee-commerce platform), to better tailor the campaign parameters designedby the marketer's own external campaign system.

FIG. 8 schematically illustrates a simplified example of aspects of themethod 700, which may be carried out by the messaging campaign engine350. In this example, a set of proposed campaign parameters (which maybe received at optional step 702) includes a set of proposed intendedrecipients 802 (identified at step 704). The set of proposed intendedrecipients 802 includes individual intended recipients 804, which may ormay not be explicitly defined in the proposed campaign parameters. Theset of proposed campaign parameters also includes a proposeddistribution channel and message content, in this example messagecontent sent via an email service 806.

Recommended campaign parameters are determined, including step 708 toidentify one or more groups 812 from the set of proposed intendedrecipients 802. In this example, groups 812 A, B and C have beenidentified. For example, the groups 812 may have been determined basedon online activity of recipients 804 (e.g., using optional step 710)and/or based on characteristics of recipients 804 (e.g., using optionalstep 712). Further, in this example group 812 C includes additionalrecipients 804 not included in the original set of proposed intendedrecipients (e.g., using optional step 714).

Using step 716, recommended parameter(s) are determined for each group812. In this simple example, the recommended parameters include arecommended distribution channel and a recommended message content foreach group 812. For group 812 A, the messaging campaign engine 350generates recommended parameters to send a first message content usingan email service 814. For group 812 B, the messaging campaign engine 350generates recommended parameters to send the first message content usinga text messaging service 816. For group 812 C, the messaging campaignengine 350 generates recommended parameters to send a second messagecontent using a social media service 818. The recommended parameters maybe provided in a single recommendation, or separate recommendations maybe used to provide each set of recommended parameters, for example.

The example method 700 described above, which may be performed using themessaging campaign engine 350 of the e-commerce platform 100, enables asingle messaging campaign to be subdivided into sub-campaigns (alsoreferred to as nested campaigns) for particular recipient groupsidentified from the initial set of intended recipients. The examplemethod 700 may provide recommended parameters (e.g., recommendeddistribution channels) that may better engage intended recipients (orgroups), by determining and recommending campaign parameters that aremore contextually relevant to the intended recipients (or groups).

The example method 700 may be used to generate and notifyrecommendations to a merchant or marketer, which the merchant ormarketer may accept or reject (or even further modify the recommendedparameters). In some examples, the disclosed method 700 may be useful togenerate recommended parameters when the merchant or marketer does notprovide a required campaign parameter (such as a distribution channel).For example, the disclosed method 700 may be used to better tailordefault campaign parameters.

In some examples, the example method 700 may be provided as an optionalor add-on service for a merchant or marketer, which may or may notrequire added premium fees for use. In some examples, an externalmarketer may use the example method 700 to supplement or complement themarketer's own external campaign generator.

FIG. 9 is a flowchart illustrating another example method 900 forgenerating a messaging campaign associated with an online store. Themethod 900 may be implemented by the e-commerce platform 100 (e.g.,using the messaging campaign engine 350 and/or the analytics facility132). The method 900 may be implemented by a processing device executinginstructions (e.g., at the core server 510 or the applications server530). The method 900 may enable dynamic (e.g., real-time or nearreal-time) modification of an ongoing messaging campaign, for example inresponse to how recipient(s) respond to messages and/or in response toother online activity by recipient(s).

At 902, a first phase of the messaging campaign is conducted (e.g.campaign messages are sent to intended recipients) according to a firstset of parameters. The first set of parameters may define a firstmessage content, a first intended recipient group, a first distributionchannel, etc. The first phase of the campaign may be conducted accordingto a campaign schedule. Although described as a “first” phase, it shouldbe understood that the method 900 is not limited to starting withstrictly the first phase of a messaging campaign. For example, if thereare three phases defined for the messaging campaign, the method 900 atstep 902 may instead start with the second of the three phases. Further,it should be understood that the method 900 may be used for a messagingcampaign that is initially defined to have only one phase. That is, step902 may be conducting the messaging campaign as a single phase, asoriginally defined, and subsequent steps of the method 900 generates anadditional second phase of the messaging campaign dynamically.

At 904, online activity of the intended recipient(s) is analyzed.Analysis of online activity may be performed similarly to step 710described above. For example, the analysis of online activity may beperformed using the analytics facility 132. The analysis of onlineactivity may also be performed using information provided by an externalsystem. At 904, the analysis of online activity includes analysis ofonline activity that takes place during the ongoing messaging campaign.

The online activity is associated with a store, which may or may not bethe store for which the messaging campaign is being conducted. Inparticular, the analysis of online activity may take into account onlineactivity across different stores (e.g., across different online storeshosted by the e-commerce platform 100), and not necessarily limited toonline activity associated with the particular store for which themessaging campaign is being conducted. Generally, online activity may beassociated with any store having an online presence, includingonline-only stores, physical stores having an online presence (e.g., astore website), and may include stores that are not hosted by thee-commerce platform 100.

The analysis of online activity includes associating online activitywith a group of intended recipients and/or individual intendedrecipient(s) (who may be part of a defined group). The analysis may begeneralized analysis (e.g., a statistical analysis of aggregate behaviorof a group) and/or may be analysis of individual behavior (e.g., wherepermission has been granted by an individual).

Information extracted from such analysis may be maintained internal tothe e-commerce platform 100 and may not be shared with merchants,customers, or external users (e.g., in order to ensure privacy andsecurity). In some examples, information from such analysis may beextracted using a machine-learning system. If a machine-learning systemis used, the extraction of analytics may be performed in a hidden layerof the machine-learning system (i.e., not part of the output provided bythe machine-learning system), such that such analytics is not explicitlyexposed even within the e-commerce platform 100.

Similarly to that described for step 710 above, the online activity thatis analyzed may include, for example, a page view event, an offeringselection event, a purchase transaction event, a product search event,an offering return event, a page share event (e.g., sharing over asocial network or other online channel), a virtual shopping cart event(e.g., an addition of an offering to the virtual shopping cart, orremoval of an offering from the virtual shopping cart), a purchaseabandonment event (e.g., starting a purchase transaction (e.g.,beginning checkout of virtual shopping cart) without completing thepurchase transaction), and/or a product review event, among otherpossibilities. In particular, analysis may include determining onlineactivity associated with purchase of an offering associated with themessaging campaign.

At 906, a second set of parameters is determined for conducting a secondphase of the messaging campaign. The determination of the second set ofparameters is based on the analysis of online activity at step 904. Thesecond set of parameters includes a change to at least one initiallydefined campaign parameter. For example, the second set of parametersmay include a change to the first set of parameters (which were used toconduct the first phase of the campaign), or the second set ofparameters may include a change to the parameters that were initiallydefined for the second phase of the campaign.

The online activity analyzed at step 904 may have a temporal alignmentwith the first phase of the messaging campaign. By “temporal alignment”,it is meant that the online activity occurs during, or shortly after(e.g., within a predetermined time interval of) the first phase of thecampaign. The temporal alignment (or temporal proximity) of the onlineactivity with the first phase of the campaign may or may not beconsidered a correlation between the online activity and the first phaseof the campaign. Even if the online activity is not considered to becorrelated with the first phase of the campaign (e.g., if the onlineactivity is viewing a website of a different online store unrelated tothe campaign), nonetheless such online activity may be taken intoaccount in determining the second set of parameters.

The determination of the second set of parameters may be based onpredefined rules (which may be developed based on historical customerbehavior) and/or using a machine-learning system.

A simple example of a set of predefined rules that may be used is: i) ifwithin one month of the first phase of the campaign, the intendedrecipient has visited the online store associated with the campaign,then in the second phase of the campaign a second message should be sentto the intended recipient within one week of the visit; ii) if theintended recipient has not visited the online store within one month ofthe first phase of the campaign, then in the second phase of thecampaign the second message should be sent at one month and shouldinclude a discount code.

A machine-learning system may be used in addition or instead ofpredefined rules. The machine-learning system (which may be implementedby the messaging campaign engine 350) can identify more sophisticatedbehavior patterns, based on historical messaging campaigns (e.g., asstored in defined campaign parameters 356) and historical engagementscores (e.g., stored in engagement metrics 358) for example. Themachine-learning system may output one or more models, which may bespecific to different groups (e.g., based on different demographics)and/or specific to different categories of merchant offerings, as thebasis for determining the second set of parameters.

Determining the second set of campaign parameters may include optionalsteps 908-914 described below. Steps 908-914 may be used in combinationfor determining the second set of campaign parameters.

Optionally, at 908, a subgroup of recipient(s) may be identified fromthe first group. The subgroup may be identified from the first groupbased on, for example, the online activity of certain members of thefirst group. For example, if certain members of the first group haveviewed the website of the online store associated with the campaign,those members may be identified as a subgroup for which a differentmessage should be communicated in the second phase than the message thatis communicated to other members (who did not view the website) of thefirst group.

In some examples, the subgroup may be considered a second recipientgroup separate from and non-overlapping with the first group. Specificrecipients may be reassigned from the first group to the second group,to enable more accurate analysis of future online activity. It may beuseful for the identified subgroup to be separated from andnon-overlapping with the original group, to avoid overlappingsub-campaigns, so that an intended recipient is not overwhelmed withmultiple messages from the same messaging campaign. In other examples,it may be useful to allow a subgroup to overlapping with the group,meaning that intended recipients who are members of the identifiedsubgroup may still be considered a member of the original group.Overlapping subgroups may be useful in situations where it would bedesirable to send multiple messages to the same intended recipientwithin the second phase of the campaign (e.g., over differentdistribution channels) to increase exposure.

In some examples, the second phase of the campaign may be conducted onlyfor the identified subgroup, and the first phase may continue to beconducted with a remainder of the first group. In other examples, thesecond phase of the campaign may be conducted for the identifiedsubgroup using the second set of parameters, and a different third setof parameters may be used to conduct the second phase for the remainderof the first group.

Optionally, at 910, the second set of parameters may include a change tothe distribution channel. For example, if the analysis of the onlineactivity shows activity related to a second distribution channel that isdifferent from the distribution channel used for the first phase of thecampaign, the second set of parameters may change the distributionchannel to match the distribution channel that shows greater activity.For example, if the first phase of the campaign involved sendingmessages via an email service, analysis of online activity may show thatmost (or all) of the group are active on social media. Accordingly, thesecond set of parameters may change the distribution channel to sendmessages in the second phase of the campaign via social media.

Optionally, at 912, the second set of parameters may include changingthe messaging schedule and/or excluding a particular subgroup so as tosuppress/delay further messaging in the second phase of the campaign.For example, analysis of online activity may indicate that one or moreintended recipients (or a subgroup) has made an online purchase (whetherat the online store associated with the campaign or at a differentstore) of the offering that was marketed by the first phase of thecampaign. Accordingly, the second phase of the campaign may excludethose recipients (or subgroup) or may suppress messaging so that therecipients (or subgroup) are not messaged again for an offering theyhave already purchased.

Optionally, at 914, the second set of parameters may include changingthe message content. This may include adding/changing/removing anincentive from the message content, changing the format (e.g., visual,audio, textual, etc.) of the message content, or changing the offeringpromoted in the message content, among other possibilities. For example,if analysis of online activity shows that an intended recipient (orsubgroup of intended recipients) mostly views online reviews having avideo component, then the message content in the second phase may bechanged to include a video. In another example, if analysis of onlineactivity shows that an intended recipient (or subgroup) has made anonline purchase of a first offering promoted in the first phase of thecampaign, then the message content in the second phase may be changed topromote a second offering that is related to the first offering.

In some examples, the step 914 may be complementary to the step 912, bysuppressing a message originally scheduled for the second phase andinstead substituting a different message for the second phase.

In some examples, a change in message content may require the merchantor marketer to provide different possible content ahead of time (e.g.,the messaging campaign engine 350 may require the merchant or marketerto provide a list of offerings to be promoted, in order to importance).In some examples, the merchant or marketer may be provided an option tosupply different message content when a recommendation is generated (atstep 916 below). In some examples, the messaging campaign engine 350 mayautomatically supply different message content based on, for example,predefined templates.

Other changes that may be made by the second set of parameters include achange in distribution channel, a change in message timing, a change innumber of messages, or a change in incentive, among other possibilities.

At 916, a recommendation is generated including the recommended secondset of parameters for the second phase of the campaign. Where a subgroupof intended recipients has been identified (e.g., at optional step 908),information about the identified subgroup may be included in therecommendation.

For privacy reasons, the recommendation that is provided to the merchantor marketer may omit identifying information about individualrecipients. For example, if the recommended campaign parameter hasidentified individuals A, B and C as belonging to a subgroup for whichmessages should be communicated via distribution channel Y in the secondphase, the merchant or marketer may only be notified that it isrecommended to change to distribution channel Y for “some” intendedrecipients.

In some examples, the recommendation may be provided to the merchant ormarketer in the form of a notification (e.g., via the user interface),and may offer an option to accept or reject the recommendation. If theoption to accept or reject is provided, the recommendation may alsoinclude a predicted success rate or historical success rate associatedwith certain recommended parameter(s) to motivate the merchant ormarketer to accept the recommended parameter(s). In some examples, therecommendation may require the merchant or marketer to provideinformation (e.g., different messaging content) in order to conduct thesecond phase according to the second set of parameters. In otherexamples, the recommendation may be automatically implemented withoutproviding an option to reject the recommendation. In some examples, therecommendation may not be explicitly provided to the merchant ormarketer, and may be automatically implemented without explicitnotification to the merchant or marketer.

Optionally, at 918, if an option to accept or reject the recommendationwas provided, a confirmation or modification of campaign parameters maybe received (e.g., via a user interface).

At 920, the second phase of the messaging campaign is conducted (e.g.campaign messages are sent to the intended recipients) using thecampaign parameters (e.g., using the second set of parameters ifaccepted). In some examples, the messaging campaign is conducted by themessaging campaign engine 350. In other examples, the messaging campaignengine 350 may output the campaign parameters to enable the messagingcampaign to be conducted by an external system. For example, a marketermay use the messaging campaign engine 350, as a service provided by thee-commerce platform 100, to dynamically tailor a campaign that isconducted using the marketer's own external campaign system.

FIGS. 10A and 10B schematically illustrate simplified examples ofaspects of the method 900, which may be carried out by the messagingcampaign engine 350. In both of these examples, a first phase 1002 ofthe messaging campaign has been conducted with a first set of campaignparameters. The first phase 1002 includes sending messages to group Aand group B (which comprise individual intended recipients 1004, who mayor may not be explicitly defined in the first set of parameters). In thefirst phase 1002, a first email message 1006 is sent to group A, and asecond email message 1008 (i.e., having different message content fromthe first email message 1006) is sent to group B.

In FIG. 10A, a second set of recommended campaign parameters aredetermined for the second phase 1012 of the campaign, including step 908to identify subgroup of recipients from the initial groups, and step 910to determine a recommended change in distribution channel. In thisexample, subgroup B2 has been identified from initial group B. Forexample, the group B2 may have been determined based on online activityof members of group B, such as being active on a social media service.Using step 910, a change to the distribution channel for subgroup B2 isdetermined. In this simple example, on the basis of subgroup B2 beingactive on the social media service, the second set of recommendedcampaign parameters include a change from distribution via email todistribution via social media 1014. The second set of recommendedcampaign parameters for conducting the second phase 1012, in this simpleexample, provides recommended changes to the campaign parameters for thegroup B, including identification of new subgroup B2, and a change inthe distribution channel for subgroup B2.

In FIG. 10B, a second set of recommended campaign parameters aredetermined for the second phase 1012 of the campaign, including step 908to identify subgroup of recipients from the initial groups, and step 912to suppress or delay the message in the second phase 1012. In thisexample, subgroup B2 has been identified from initial group B. Forexample, the group B2 may have been determined based on online activityof members of group B, such as having made an online purchase of theoffering promoted in the first phase 1002. Using step 912, an exclusionof subgroup B2 or a suppression of further messages for subgroup B2 inthe second phase 1012 is determined. In this simple example, on thebasis of subgroup B2 having already purchased the promoted offering, thesecond set of recommended campaign parameters include excluding subgroupB2 or suppressing further messages 1016 to subgroup B2 in the secondphase. The second set of recommended campaign parameters for conductingthe second phase 1012, in this simple example, provides recommendedchanges to the campaign parameters for the group B, includingidentification of new subgroup B2, and an exclusion of subgroup B2 fromgroup B or a suppression of further messages to the subgroup B2.

The example method 900 described above, which may be performed using themessaging campaign engine 350 of the e-commerce platform 100, enablesdynamic (e.g., real-time or near real-time) adjusting of a messagingcampaign, based on real-time monitoring and analysis of online activityof intended recipient(s) (or group(s) of intended recipient(s)). Theexample method 900 may provide recommendations that may better engageintended recipients (or groups), by determining and recommendingcampaign parameters over the duration of the messaging campaign that arerelevant, based on temporally aligned online activity of the intendedrecipients (or groups).

The example method 900 may provide recommended parameters that maybetter engage intended recipients (or groups) over the lifetime of amessaging campaign, by dynamically adjusting the campaign parametersover multiple phases of the campaign.

In some examples, the example method 900 may be provided as an optionalor add-on service for a merchant or marketer, which may or may notrequire added premium fees for use. In some examples, an externalmarketer may use the example method 900 to monitor and adjust a campaignconducted by the marketer's own external campaign generator.

In some examples, the example methods 700 and 900 may be used togetherto conduct a single messaging campaign. For example, the method 700 mayfirst be used to generate a first set of campaign parameters and conductthe first phase of a messaging campaign over multiple distributionchannels, then the method 900 may be used to dynamically generate asecond set of campaign parameters for conducting the second phase of themessaging campaign, for example tailoring the message by changing thedistribution channel for some subgroup of intended recipients.

In various examples discussed herein, methods and systems are providedfor generating and conducting a messaging campaign. Instead of relyingon a merchant or marketer to select the campaign parameters (e.g.,select a distribution channel) which are fixed over the duration of thecampaign, aspects of the present disclosure enable a campaign to bedivided into sub-campaigns that are better directed towards certainrecipients (or recipient groups). Recipients can be dynamically groupedinto specific subgroups depending on their online activity during thetimeframe of the campaign.

The disclosed methods and systems enable analysis of online activity,not limited to any specific messaging campaign, to determinerecommendations for tailoring a proposed and/or ongoing messagingcampaign. Further, such analysis may be anonymized and/or categorizedbased on recipient characteristics, offering categories, storecategories, etc.

Using examples of the disclosed methods and systems, the e-commerceplatform 100 may enable a merchant or marketer to leverage analyticsgenerated from multiple historical campaigns. This may be of particularvalue to less-experienced merchants or marketers. The recommendationsprovided by the e-commerce platform 100 may include information aboutintended recipient groups, online activity and/or historical successrates, etc. which may help to educate the merchant or marketer fordesigning future messaging campaigns.

Although the present disclosure describes methods and processes withsteps in a certain order, one or more steps of the methods and processesmay be omitted or altered as appropriate. One or more steps may takeplace in an order other than that in which they are described, asappropriate.

Although the present disclosure is described, at least in part, in termsof methods, a person of ordinary skill in the art will understand thatthe present disclosure is also directed to the various components forperforming at least some of the aspects and features of the describedmethods, be it by way of hardware components, software or anycombination of the two. Accordingly, the technical solution of thepresent disclosure may be embodied in the form of a software product. Asuitable software product may be stored in a pre-recorded storage deviceor other similar non-volatile or non-transitory computer readablemedium, including DVDs, CD-ROMs, USB flash disk, a removable hard disk,or other storage media, for example. The software product includesinstructions tangibly stored thereon that enable a processing device(e.g., a personal computer, a server, or a network device) to executeexamples of the methods disclosed herein.

The present disclosure may be embodied in other specific forms withoutdeparting from the subject matter of the claims. The described exampleembodiments are to be considered in all respects as being onlyillustrative and not restrictive. Selected features from one or more ofthe above-described embodiments may be combined to create alternativeembodiments not explicitly described, features suitable for suchcombinations being understood within the scope of this disclosure.

All values and sub-ranges within disclosed ranges are also disclosed.Also, although the systems, devices and processes disclosed and shownherein may comprise a specific number of elements/components, thesystems, devices and assemblies could be modified to include additionalor fewer of such elements/components. For example, although any of theelements/components disclosed may be referenced as being singular, theembodiments disclosed herein could be modified to include a plurality ofsuch elements/components. The subject matter described herein intends tocover and embrace all suitable changes in technology.

All referenced documents are hereby incorporated by reference in theirentireties.

1. A system comprising: a processor in communication with a storage, theprocessor configured to execute instructions in the storage to cause thesystem to: conduct a messaging campaign over at least a first phase anda second phase, the first and second phases being separated temporallybased on a schedule associated with the messaging campaign, wherein theprocessor is configured to execute the instructions for conducting themessaging campaign to cause the system to: conduct the first phase ofthe messaging campaign, the first phase including a first set ofparameters for delivering a first message to at least a first group ofintended recipients, the first set of parameters defining at least thefirst group and a respective first distribution channel; responsive toconducting the first phase of the messaging campaign, determine, basedon analysis of online activity associated with one or more members ofthe first group, the online activity occurring in temporal alignmentwith the first phase of the campaign and being associated with a store,a second set of parameters for the second phase of the messagingcampaign, the second set of parameters defining a change to the firstset of parameters for delivering a second message to the one or moremembers; and prior to conducting the second phase of the messagingcampaign, generate a recommendation to conduct the second phase of themessaging campaign for the one or more members using the second set ofparameters.
 2. The system of claim 1, wherein the analysis of the onlineactivity comprises analysis of at least one of: online activityassociated with a first store associated with the messaging campaign, oronline activity associated with a second store not associated with themessaging campaign.
 3. The system of claim 1, wherein the onlineactivity is associated with a purchase of a first offering associatedwith the messaging campaign.
 4. The system of claim 3, wherein theprocessor is configured to execute instructions to cause the system to:determine the second set of parameters to suppress promotion of thefirst offering to the one or more members in the second phase of themessaging campaign.
 5. The system of claim 3, wherein the processor isconfigured to execute instructions to cause the system to: determine thesecond set of parameters to promote a second offering, that is relatedto the first offering, to the one or more members in the second phase ofthe messaging campaign.
 6. The system of claim 1, wherein the one ormore members define a subgroup of the first group, and wherein theprocessor is configured to execute instructions to cause the system to:conduct the second phase of the messaging campaign according to thesecond set of parameters for the subgroup; and continue conducting thefirst phase of the messaging campaign according to the first set ofparameters for a remainder of the first group.
 7. The system of claim 1,wherein the one or more members define a subgroup of the first group,and wherein the processor is configured to execute instructions to causethe system to: conduct the second phase of the messaging campaign forthe subgroup, according to the second set of parameters; and conduct thesecond phase of the messaging campaign for a remainder of the firstgroup according to a third set of parameters.
 8. The system of claim 1,wherein the second set of parameters is defined for conducting themessaging campaign to a second group of intended recipients, and whereinthe processor is configured to execute instructions to cause the systemto reassign the one or more members to the second group.
 9. The systemof claim 1, wherein the online activity comprises at least one of: apage view event; a purchase transaction event; an offering search event;or a product review event.
 10. The system of claim 1, wherein the changedefined by the second set of parameters comprises at least one of: achange in distribution channel; a change in message content; a change inmessage timing; a change in number of messages; or a change inincentive.
 11. The system of claim 1, wherein the processor isconfigured to execute instructions to cause the system to: associate theonline activity with a second distribution channel; and determine thesecond set of parameters to deliver the second message using the seconddistribution channel.
 12. The system of claim 1, wherein the processoris configured to execute instructions to cause the system to:automatically implement the recommendation to conduct the second phaseof the messaging campaign for the one or more members using the secondset of parameters.
 13. A computer-implemented method comprising:conducting, by a computing platform, a messaging campaign over at leasta first phase and a second phase, the first and second phases beingseparated temporally based on a schedule associated with the messagingcampaign, wherein conducting the messaging campaign comprises:conducting the first phase of the messaging campaign, the first phaseincluding a first set of parameters for delivering a first message to atleast a first group of intended recipients, the first set of parametersdefining at least the first group and a respective first distributionchannel; responsive to conducting the first phase of the messagingcampaign, determining, based on analysis of online activity associatedwith one or more members of the first group, the online activityoccurring in temporal alignment with the first phase of the campaign andbeing associated with a store, a second set of parameters for the secondphase of the messaging campaign, the second set of parameters defining achange to the first set of parameters for delivering a second message tothe one or more members; and prior to conducting the second phase of themessaging campaign, generating a recommendation to conduct the secondphase of the messaging campaign for the one or more members using thesecond set of parameters.
 14. The computer-implemented method of claim13, wherein the analysis of the online activity comprises analysis of atleast one of: online activity associated with a first store associatedwith the messaging campaign, or online activity associated with a secondstore not associated with the messaging campaign.
 15. Thecomputer-implemented method of claim 13, wherein the online activity isassociated with a purchase of a first offering associated with themessaging campaign, and the second set of parameters is determined tosuppress promotion of the first offering to the one or more members inthe second phase of the messaging campaign.
 16. The computer-implementedmethod of claim 13, wherein the online activity is associated with apurchase of a first offering associated with the messaging campaign, andthe second set of parameters is determined to promote a second offering,that is related to the first offering, to the one or more members in thesecond phase of the messaging campaign.
 17. The computer-implementedmethod of claim 13, wherein the online activity comprises at least oneof: a page view event; a purchase transaction event; an offering searchevent; or a product review event.
 18. The computer-implemented method ofclaim 13, further comprising: associating the online activity with asecond distribution channel; and determining the second set ofparameters to deliver the second message using the second distributionchannel.
 19. The computer-implemented method of claim 13, furthercomprising: automatically implementing the recommendation to conduct thesecond phase of the messaging campaign for the one or more members usingthe second set of parameters.
 20. A non-transitory computer readablemedium having computer-executable instructions stored thereon, whereinthe instructions, when executed by a processor of a system, causes thesystem to: conduct a messaging campaign over at least a first phase anda second phase, the first and second phases being separated temporallybased on a schedule associated with the messaging campaign, wherein theinstructions for conducting the messaging campaign cause the system to:conduct the first phase of the messaging campaign, the first phaseincluding a first set of parameters for delivering a first message to atleast a first group of intended recipients, the first set of parametersdefining at least the first group and a respective first distributionchannel; responsive to conducting the first phase of the messagingcampaign, determine, based on analysis of online activity associatedwith one or more members of the first group, the online activityoccurring in temporal alignment with the first phase of the campaign andbeing associated with a store, a second set of parameters for the secondphase of the messaging campaign, the second set of parameters defining achange to the first set of parameters for delivering a second message tothe one or more members; and prior to conducting the second phase of themessaging campaign, generate a recommendation to conduct the secondphase of the messaging campaign for the one or more members using thesecond set of parameters.